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Detecting Low-level Radiation Sources Using Border Monitoring Gamma Sensors...

by Satyabrata Sen, Nageswara S Rao, Chase Wu, Richard Brooks, Christopher Temples
Publication Type
Conference Paper
Book Title
Proceedings of IEEE International Conference on Multisensor Fusion and Integration (MFI 2020)
Publication Date
Page Numbers
1 to 6
Publisher Location
Piscatawy, New Jersey, United States of America
Conference Name
IEEE International Conference on Multisensor Fusion and Integration (MFI 2020)
Conference Location
Karlsruhe, Germany
Conference Sponsor
Conference Date

We consider a problem of detecting a low-level radiation source using a network of Gamma spectral sensors placed on the periphery of a monitored region. We propose a computationally light-weight, correlation-based method which is primarily intended for systems with limited computing capacity. Sensor measurements are combined at the fusion by first generating decisions at each time step and then taking their majority vote within a time widow. At each time step, decisions are generated using two strategies: (i) SUM method based on a threshold decision on a correlation statistic derived from measurements from all sensors, and (ii) OR method based on logical-OR of threshold decisions based on correlations statistics of individual sensor measurements. We derive analytical performance bounds for false alarm rates of SUM and OR methods, and show that their performance is enhanced by the temporal smoothing of majority vote within a time window. Using measurements from a test campaign, we generate a border monitoring scenario with twelve 2"x2" NaI Gamma sensors deployed on the periphery of 42m x 42m outdoor region. A Cs-137 source is moved in a straight-line across this region, starting several meters outside and finally moving away from it. We illustrate the performance of both correlation-based detection methods, and compare their performances with each other and with a particle filter method. Overall, under small false-alarm conditions, the OR fusion is found to produce better detection performance.